Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …

The vast majority of today's data is collected and stored in enormous databases with a wide
range of characteristics that have little to do with the overarching goal concept. Feature …

The shuffled frog leaping algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …

Abstract Grey Wolf Optimizer (GWO) is a new swarm intelligence algorithm mimicking the
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …

Because of their high dimensionality, dealing with large datasets can hinder the data mining
process. Thus, the feature selection is a pre-process mandatory phase for reducing the …

Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

Feature selection (FS) is a machine learning process commonly used to reduce the high
dimensionality problems of datasets. This task permits to extract the most representative …

Feature selection is a significant task in data mining and machine learning applications
which eliminates irrelevant and redundant features and improves learning performance. In …

Crow search algorithm (CSA) is a new natural inspired algorithm proposed by Askarzadeh
in 2016. The main inspiration of CSA came from crow search mechanism for hiding their …